Summary
Overview
Work History
Education
Skills
Interests
PUBLICATIONS
Timeline
Generic
Yaghik Pandey

Yaghik Pandey

Clayton

Summary

Results-driven Data Analyst and Machine Learning Enthusiast with expertise in Python, SQL, and predictive analytics, experienced in leveraging data-driven insights for business optimization. Background in fintech and consulting, improving product engagement, campaign efficiency, and reporting automation. Skilled in cloud computing, visualization, and end-to-end data pipelines. Co-author of an IEEE publication on a full-stack donation platform. Currently pursuing a Master’s in Data Science at Monash University, focused on integrating AI, big data, and automation into practical, scalable business solutions.

Overview

5
5
years of professional experience

Work History

Director & Datathon Officer

Monash Data Science and AI Society
11.2024 - Current
  • Currently serving as Director (since Sep 2025), leading a team of four officers to plan and execute workshops, hackathons.
  • Overseeing event pipelines, mentorship programs, and cross-society collaborations, fostering a hands-on data culture at Monash.
  • Designed and delivered technical workshops on topics including:
  • Machine Learning Workflow (50+ attendees) Data cleaning, EDA, and model evaluation.
  • Business Analytics & CLTV Modeling (35+ participants) Customer behavior, RFM modeling, A/B testing.
  • Developed interactive, case-driven content bridging technical analysis and business impact.

Data Analyst

Mobikwik
03.2023 - 07.2024
  • Optimized 10+ dashboards and reports for Key Performance Indicators, improving reporting efficiency by 15%.
  • Analyzed product features, user behaviour and journey to recommend 5+ feature enhancements, leading to a 10% improvement in user retention in a year.
  • Evaluated user events such as churn, conversion, and drop-off, reducing churn rates by 10% through targeted insights.
  • Analyzed customer cross-sell behavior, strategized 10+ campaigns, and achieved a 5% increase in user movement between products.
  • Worked with Decision Tree algorithms to analyze correlations between Ad Spends, TOF (Top of Funnel), Conversion Rates, and Transactions. Identified seasonality effects and answered critical business questions such as "What is the minimum ad spend required to yield a transaction", driving 7% optimization in ad spend efficiency.

Assistant Manager - Data Science

Deloitte
08.2022 - 02.2023
  • Developed analytics dashboards that reduced reporting time by 30% and improved business insights for stakeholders.
  • Optimized data storage and query performance, achieving 30% faster query execution and reducing storage costs by 20%.
  • Conducted code reviews and bug diagnosis, improving data accuracy and ensuring seamless data flow.
  • Processed and analyzed large datasets (50M+ records) to uncover revenue trends and identify data anomalies.
  • Built a payroll anomaly preprocessing tool, reducing manual effort by 50%.

Delivery Analyst

Cartesian Consulting
04.2021 - 08.2022
  • Developed automated data quality assurance solutions, improving data accuracy by 8% and reducing processing time by 20%.
  • Analyzed user segments, leading to a 15% increase in customer engagement through targeted strategies.
  • Built and optimized a CLTV model, accurately predicting 85%+ of high-value customers and enabling a 10% increase in revenue from retention campaigns.
  • Conducted Market Basket Analysis, identifying key product associations and influencing 5% uplift in cross-sell revenue.

Education

Master of Data Science -

Monash University
10.2025

Postgraduate Certificate - Applied Data Science & Machine Intelligence

IIT Madras
06.2023

Bachelor of Engineering - Computer Science

University of Petroleum & Energy Studies
01.2020

Skills

  • Languages: Python, SQL, Scala, JavaScript, ReactJS, Java, R
  • Libraries: Pandas, NumPy, Matplotlib, Seaborn, Plotly, Keras, TensorFlow, PySpark, Shiny
  • Tools: Power BI, Airflow, Databricks, MS Office, Git
  • Cloud: AWS, Azure
  • Mathematics: Statistics, Probability, Linear Algebra, Calculus
  • ML Techniques: Supervised & Unsupervised Learning, Feature Engineering, Model Evaluation

Interests

Exploring and learning about emerging and upcoming technologies to stay updated with industry trends
Enjoying walks in peaceful and calm environments, which help refresh the mind and spark new ideas
Practicing meditation regularly to enhance focus, creativity, and inner peace

PUBLICATIONS

  • PARHIT: An Innovative Full-Stack Donation Platform with Dynamic-Routing Approach in ReactJS
  • Co-authored the paper published in IEEE – 2023 7th International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)
  • The objective was to simplify the donation process by expediting the collection and distribution of old items so that they reach the appropriate organizations or individuals in a timely manner.
  • Implemented dynamic routing in ReactJS for seamless user navigation.
  • Implemented features like user authentication and secure data storage management using Firebase.
  • Paper Link: https://ieeexplore.ieee.org/document/10304893

Timeline

Director & Datathon Officer

Monash Data Science and AI Society
11.2024 - Current

Data Analyst

Mobikwik
03.2023 - 07.2024

Assistant Manager - Data Science

Deloitte
08.2022 - 02.2023

Delivery Analyst

Cartesian Consulting
04.2021 - 08.2022

Postgraduate Certificate - Applied Data Science & Machine Intelligence

IIT Madras

Bachelor of Engineering - Computer Science

University of Petroleum & Energy Studies

Master of Data Science -

Monash University
Yaghik Pandey